Automatic quality control method for production line and apparatus therefor as well as automatic quality control program

ABSTRACT

Production condition data and product quality data in a production line are monitored and stored in a production history database. When a quality deterioration event in the production line is detected while checking the product quality data, the improvement contents of the quality deterioration factor and production conditions are extracted. The extracted results and pre-stored quality improvement history data are collated with each other in order to confirm the validity thereof, and a simulation of the phenomenon of the production line is executed in order to verify the correctness. When the validity and correctness are verified, the production condition for the production line are revised to improve the quality deterioration factor.

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application is based upon and claims the benefit of priorityfrom the prior Japanese Patent Application No. 2000-338214, filed Nov.6, 2000, the entire contents of which are incorporated herein byreference.

BACKGROUND OF THE INVENTION

[0002] 1. Field of the Invention

[0003] The present invention relates to a quality control method for aproduction line which automatically carries out quality control of theline, which can be applied to various types of production lines such aslines for color-cathode ray tubes and semiconductor devices, and anapparatus used for the method, as well as an automatic quality controlprogram.

[0004] 2. Description of the Related Art

[0005] Production lines are designed for various types of products suchas color cathode ray tubes and semiconductor devices. In the productionlines, the quality of the products is controlled while they areproduced.

[0006] In quality control, first, data indicating the quality of part ofthe products out of a great number produced on the line is sampled. Theproduct quality data includes the results of tests carried out onproducts in accordance with their type, for example, the results ofperformance tests of the product or the results of the examination ofthe appearance.

[0007] Next, the overall distribution and the degree of dispersion ofthe sampling data are obtained. Then, the relationship between theproduction condition for a product and the product quality is graspedfrom the overall distribution and the degree of dispersion. Thus, fromthe relationship between the production condition and the productquality, the quality of the product is controlled.

[0008] In the quality control of a product, there is a method in whichdetailed examination data of the product is sampled, and defect analysisof the product is carried out by using this sampling data.

[0009] However, in many cases, the just-mentioned quality control methodcan only be performed by operators highly skilled in manipulation,adjustment and operation of the production line. That is, operators, whohave extensive and long-term experience regarding the product andproduction on the production line, lean an empirical rule specially foroperating the production line and have obtained skills for improving theproduction line.

[0010] At present, the technology for monitoring network databases, etc.has been developed, and therefore the quality management of the productis conducted on the basis of the database. In quality control,identification data such as a bar code is assigned to each and every oneof the products conveyed on the production line, and the productioncondition data and the quality data of each and every product is stored.In this manner, quality control of the individual products can berelatively easily achieved.

[0011] In product quality control, if a great amount of data (productionhistory data) such as production conditions and product quality of agreat number of products produced is utilized effectively, it isconsidered possible to achieve more precise control over the quality.

[0012] However, there is a certain limit to the data processing abilityof human being. Further, in the defect analysis of the products on thebasis of the detailed data, the gauge of the analysis, in many cases,depends on the judgment and/or intuition of the operator who has aspecial empirical rule and an improving skill, and therefore theeffective application of the data is further interrupted.

[0013] To summarize, with the quality control method for products, whichconventionally much depends on the human factors, it is difficult tocontrol the quality of the products by effectively making a full use ofa huge amount of product history data of a great number of products.

[0014] Under the circumstances, the object of the present invention isto provide an automatic quality control method for a production line,which can effectively make a full use of a huge amount of data byovercoming the limits of the data processing capabilities of humansystems or the ambiguities innate to empirical and intuitive methods ofhumans, and the apparatus therefor, as well as an automatic qualitycontrol program.

BRIEF SUMMARY OF THE INVENTION

[0015] According to an aspect of the present invention, there isprovided an automatic quality control method for a production line,comprising: monitoring a plurality of production condition data formanufacturing products from a production line and product quality dataindicating quality of manufactured products; storing the productioncondition data and product quality data thus monitored in a database;checking the production condition data to detect whether or not there isan event which deteriorates the quality of products; extracting, if aquality deteriorating event is detected, a quality deteriorating factorwhich causes the quality deteriorating event and improvement contents ofproduction conditions against the quality deteriorating factor on thebasis of the quality deteriorating event and the production conditiondata; collating the quality deteriorating factor and improvementcontents thus extracted with improvement examples pre-stored forpossible quality deteriorating factors and confirming the validity ofthe quality deteriorating factor and improvement contents; executing asimulation of manufacture of a product in the production line based onthe quality deteriorating factor and improvement contents thusextracted, and verifying the correctness of the quality deterioratingfactor and the validity of the improvement contents, extracted from theresult of the simulation; and if the correctness of the qualitydeteriorating factor and the validity of the improvement contents areverified, the production conditions for the production line inaccordance with the improvement contents.

[0016] According to another aspect of the present invention, there isprovided an automatic quality control apparatus for a production line,comprising: a production line configured to produce products; a firstdatabase configured to store a plurality of production condition datafor producing the products and product quality data indicating qualityof the products; a monitoring section configured to monitor a pluralityof product condition data for production the products from theproduction line and further monitor the product quality data indicatingthe quality of the products, to store them in the first database; anextraction section configured to check the production condition data todetect whether or not there is an event which deteriorate the quality ofproducts, and to extract a quality deteriorating factor which causes thequality deteriorating event and improvement contents of productionconditions regarding the quality deteriorating factor on the basis ofthe quality deteriorating event and the production condition data; asecond database configured to store, in advance, improvement examplesfor the quality deterioration factor; a validity confirming sectionconfigured to confirm the validity of the quality deteriorating factorand improvement contents by collating the quality deteriorating factorand improvement contents extracted by the extracting section with theimprovement examples pre-stored in the second database; a verifyingsection configured to execute a simulation of production of the productsin the production line under current production conditions, and toverify the correctness of the quality deteriorating factor and thevalidity of the improvement contents from a result of the simulation;and a feedback control section configured to revise the productionconditions for the production line in accordance with the improvementcontents when the correctness of the quality deteriorating factor andthe validity of the improvement contents are verified.

[0017] According to still another aspect of the present invention, thereis provided an automatic quality control program for a production line,comprising: monitoring a plurality of production condition data formanufacturing color cathode ray tubes from a production line and productquality data indicating quality of manufactured products; storing theproduction condition data and product quality data thus monitored in adatabase; checking the production condition data to detect whether ornot there is an event which deteriorate the quality of products;extracting, if a quality deteriorating event is detected, a qualitydeteriorating factor which causes the quality deteriorating event andimprovement contents of production conditions against the qualitydeteriorating factor on the basis of the quality deteriorating event andthe production condition data; collating the quality deterioratingfactor and improvement contents thus extracted with improvement examplespre-stored for possible quality deteriorating factors and confirming thevalidity of the quality deteriorating factor and improvement contents;executing a simulation of manufacture of a product in the productionline based on the quality deteriorating factor and improvement contentsthus extracted, and verifying the correctness of the qualitydeteriorating factor and the validity of the improvement contents,extracted from the result of the simulation; and if the correctness ofthe quality deteriorating factor and the validity of the improvementcontents are verified, the production conditions for the production linein accordance with the improvement contents.

[0018] As described above, there is provided, according to the presentinvention, an automatic quality control method for a production line,which can effectively make a full use of a huge amount of data byovercoming the limits of the data processing capabilities of humansystems or the ambiguities innate to empirical and intuitive methods ofhumans, and the apparatus therefor, as well as an automatic qualitycontrol program.

[0019] Additional objects and advantages of the invention will be setforth in the description which follows, and in part will be obvious fromthe description, or may be learned by practice of the invention. Theobjects and advantages of the invention may be realized and obtained bymeans of the instrumentalities and combinations particularly pointed outhereinafter.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING

[0020] The accompanying drawings, which are incorporated in andconstitute a part of the specification, illustrate embodiments of theinvention, and together with the general description given above and thedetailed description of the embodiments given below, serve to explainthe principles of the invention.

[0021]FIG. 1 is a block diagram showing a structure of a firstembodiment of an automatic quality control apparatus for a productionline, according to the present invention;

[0022]FIG. 2 is a diagram showing a production line for a color-cathoderay tube, which is applied to the first embodiment of the automaticquality control apparatus for a production line, according to thepresent invention;

[0023]FIG. 3 is a diagram showing a procedure of an automatic qualitycontrol program in the first embodiment of the automatic quality controlapparatus for a production line, according to the present invention;

[0024]FIG. 4 is a schematic diagram showing production condition dataand product quality data in the first embodiment of the automaticquality control apparatus for a production line, according to thepresent invention;

[0025]FIG. 5 is a schematic diagram showing a quality improvementhistory database in the first embodiment of the automatic qualitycontrol apparatus for a production line, according to the presentinvention;

[0026]FIG. 6 is a block diagram showing a structure of a secondembodiment of an automatic quality control apparatus for a productionline, according to the present invention; and

[0027]FIG. 7 is a block diagram showing a structure of a thirdembodiment of an automatic quality control apparatus for a productionline, according to the present invention.

DETAILED DESCRIPTION OF THE INVENTION

[0028] The first embodiment of the present invention will now bedescribed with reference to accompanying drawings.

[0029]FIG. 1 is a block diagram showing a structure of an automaticquality control apparatus for a production line. A production line 1 isan example of a generally known production line for a color cathode raytube. The production line 1, as shown in FIG. 2, includes a panel maskassembly process 2, a black body application process 3, a micro-filterapplication process 4, a fluorescent material application process 5, asealing/enclosing/exhaustion process 6, a yoke assembly adjustmentprocess 7 and an examination process 8.

[0030] The production conditions for the color cathode ray tube in theproduction line 1 are, for example, the outside temperature, humidity,the hot water ejection time for ejecting hot water to the glass panel ofthe color cathode ray tube, the kinetic viscosity of the solution usedfor applying the fluorescent material, and the amount of the fluorescentmaterial applied. Other than these, there are a great number ofproduction conditions for the color cathode ray tube.

[0031] A production condition control section 9 controls each of aplurality of production conditions in the production line 1 forproducing color cathode ray tubes.

[0032] Another example of the production line 1 is a line forsemiconductor devices. The production line 1 for semiconductor devicesincludes, for example, a film forming process, a resist applicationprocess, an exposure process, development process, an etching processand a resist removing process.

[0033] A production condition control section 9 of the production linefor semiconductor devices controls, for example, the temperature,humidity, resist viscosity, application force of the resist, and theapplication amount of the resist, with regard to the production line 1for semiconductor devices.

[0034] The production line 1 is not limited to the manufacture of colorcathode ray tubes or semiconductor devices, but it can be a line for avariety of types of products.

[0035] An arithmetic operating section 10 is connected to a programmemory 11, a production history database 12 and a quality improvementhistory database 13.

[0036] The program memory 11 stores an automatic quality controlprogram. The details of the automatic quality control program, whichwill be described in detail later, include the following sevenprocedures.

[0037] That is:

[0038] (1) The first procedure (step #1) in which a plurality ofproduction condition data for manufacturing color cathode ray tubes aremonitored from the production line 1 and product quality data indicatingthe qualities of manufactured products are monitored;

[0039] (2) The second procedure (step #2) in which the productioncondition data and product quality data thus monitored are stored in theproduction history database 12;

[0040] (3) The third procedure (step #3) in which the productioncondition data are monitored and whether or not there is an event whichdeteriorates the quality of products is detected;

[0041] (4) The fourth procedure (step #4) in which if a qualitydeteriorating event is detected, a quality deteriorating factor whichcauses the quality deteriorating event and improvement contents ofproduction conditions against the quality deteriorating factor areextracted on the basis of the quality deteriorating event and theproduction condition data;

[0042] (5) The fifth procedure (step #5) in which the qualitydeteriorating factor and improvement contents thus extracted arecollated with improvement examples pre-stored for possible qualitydeteriorating factors to confirm the validity of the qualitydeteriorating factor and improvement contents;

[0043] (6) The sixth procedure (step #6) in which a simulation ofmanufacture of a product is executed in the production line 1 based onthe quality deteriorating factor and improvement contents thusextracted, to verify the correctness of the quality deteriorating factorand the validity of the improvement contents, extracted from the resultof the simulation; and

[0044] (7) The seventh procedure (step #7) in which if the correctnessof the quality deteriorating factor and the validity of the improvementcontents are verified, the production conditions for the production line1 are revised in accordance with the improvement contents.

[0045] The arithmetic operating section 10 is designed to execute theautomatic quality control program stored in the program memory 11, andincludes a monitoring section 14, an extracting section 15, a validityconfirming section 16, a verifying section 17, a feedback controlsection 18 and a regional feedback control section 19.

[0046] The monitoring section 14 monitors a plurality of productioncondition data and product quality data in the production line 1, andstores these product quality data in the production history database 12.

[0047] The monitoring section 14 monitors production condition data fromeach of a plurality of processes in the line 1 for color cathode raytube shown in, for example, FIG. 2, such as the black dye applicationprocess 3, the micro-filter application process 4 and the fluorescentmaterial application process 5.

[0048] Further, the monitoring section 14 monitors product quality datafrom each of a plurality of processes in the line 1 for color cathoderay tube shown in, for example, FIG. 2, such as the fluorescent materialapplication process 5 and the examination process 8.

[0049] If the production condition data and the product quality data aredocuments, the monitoring section 14 creates an electronic file 14 a(electronified document) from the documents, and stores it in theproduction history database 12.

[0050] If the production condition data and the product quality data aresensor signals, the monitoring section 14 monitors the sensor signalsand converts them into digital signals (digital sensor signals 14 b),and stores the digital signal in the production history database 12.

[0051] If the production condition data and the product quality data areimages, the monitoring section 14 carries out pattern recognition 14 con the images, and stores them in the production history database 12.

[0052] If the production condition data and the product quality data aresensed amount by human (operator), the monitoring section 14 convertsthe sensed amount into a numerical value (conversion of sensed amountinto numeral 14 d) according to a specific algorithm, and stores it inthe production history database 12.

[0053] The production history database 12 stores the productioncondition data 20 and the product quality data 21 shown in FIG. 4.

[0054] In the case of manufacture of color cathode ray tube, theproduction condition data 20 include the serial number (serial No.) ofeach color cathode ray tube, the date, the outside temperature, thehumidity, the hot water ejecting time, the kinetic viscosity of thefluorescent material slurry, the application amount of the fluorescentmaterial slurry and the like, as shown in FIG. 4.

[0055] In the case of manufacture of semiconductor devices, theproduction condition data 20 include the serial number (serial No.) ofeach semiconductor device, the date, the temperature, the humidity, theviscosity of the resist, the application force of the resist and thelike.

[0056] Other than those mentioned above, the production condition data20 include the flow amount of the process gas and the pressure thereof.

[0057] The product quality data 21 indicate the quality of a producedcolor cathode ray tube. The product quality data 21 include the judgmentresult data, the examination result data and the quality data.

[0058] The judgment result data indicates whether or not the appearanceand function of the produced color cathode ray tube are respectivelythose as designed in advance.

[0059] The quality data indicates the yield in the manufacture of colorcathode ray tubes, and the percent defective in the color cathode raytubes.

[0060] A specific example of the product quality data 21 is to indicatehow white the screen is displayed when a white color is displayed on thescreen of the color cathode ray tube. In this case, if the displayedscreen is not a white color of a certain degree, an error codeindicating a whitening error is stored.

[0061] The extraction section 15 checks the product quality data 21stored in the production history database 12, and detects whether or notthere is a quality deterioration event (error code) in the manufactureof the color cathode ray tubes. The items to be detected while checkingthe product quality data 21 are a sudden variation in the occurrencerate of the quality deterioration event as well as whether or not theyield of the color cathode ray tubes stays at the level of the originalyield.

[0062] For example, a sudden variation in the occurrence rate of thequality deterioration event can be detected, for example, by obtainingthe occurrence rate of an error code and watching if the occurrence rateabruptly increases within a certain time period.

[0063] Whether or not a yield stays at its original level, can bedetected, for example, by obtaining the yield of color cathode ray tubesfrom the occurrence of an error code and watching if the yield stays atits original level along with time elapse.

[0064] When a sudden variation in the occurrence rate of the qualitydeterioration event or the staying of a yield at its original level isdetected, the extracting section 15 extracts the quality deteriorationfactor which causes the quality deterioration event and the improvementcontents of the production condition data 20 for the qualitydeterioration factor, based on the quality deterioration factor and theproduction condition data 20.

[0065] More specifically, the extracting section 15 executes a datamining algorithm on the bases of the quality deterioration event and theproduction condition data, and extracts the improvement contents.

[0066] The data mining algorithm is a processing procedure, by way ofexecuting a software, for extracting useful data from a huge amount ofproduction condition data 20 and product quality data 21 stored in theproduction history database 12 using various types of methods such as astatistical method, an artificial intelligence (AI) method and a machinelearning method.

[0067] Typical and specific examples of the data mining algorithm interms of the statistical method are correlation analysis, multipleregression analysis and variance analysis. In terms of the artificialintelligence (AI) method, an example thereof is an analysis of thesignificance of a factor by neural network leaning. In terms of themachine leaning method, an example thereof is a process ofclassification based on various types of indexes such as a square valueof χ, the entropy of data and the purity of data.

[0068] The quality improvement history database 13 stores improvementexamples for quality deterioration factors in advance. In specific, thequality improvement history database 13 stores already known factors forthe occurrence of errors and a decrease in the yield, and improvementexamples as quality improvement history data. Naturally, the qualityimprovement history data have been digitized.

[0069] The quality improvement history data, which includes qualitydeterioration factors, the contents of the quality deterioration factorsand the improvement contents for the quality deterioration factors, arestored in the form of, for example, “if-then” expression. FIG. 5 is aschematic diagram of the quality improvement history database 13. Thequality improvement history data includes, for example, the date, thecontents of the quality deterioration (error code), the deteriorationfactors, the improvement contents and the improvement results. Forexample, the following items are stored. That is, the column of the dateindicating “2001/11/6”, the column of the quality deterioration contentsindicating “frequent occurrence of irregularity of the red fluorescentmaterial of color cathode ray tube” the column of the deteriorationfactors indicating “low external temperature and high kineticviscosity”, the column of the improvement contents indicating “extensionof hot water ejection and change in upper limit of kinetic viscosity”and the column of the improvement results indicating “error occurrencerate back to normal”.

[0070] The validity confirming section 16 collates the qualitydeterioration factor and the improvement contents extracted from theextracting section 15 with the quality improvement history datapre-stored in the quality deterioration history database 13, in order toconfirm the validity of the quality deterioration factor and theimprovement contents.

[0071] The verifying section 17 executes a simulation of a phenomenonregarding the production line 1 according to the quality deteriorationfactor and the improvement contents extracted by the extracting section15, that is, a simulation for analyzing a basic physiochemicalphenomenon regarding the manufacture of color cathode ray tubes. Fromthe result of the simulation, the correctness of the qualitydeterioration factor and the validity of the improvement contents areverified.

[0072] In other words, the verifying section 17 verifies if the qualitydeterioration factor extracted by the extracting section 15 is correct.The section further verifies, when the production condition data of theproduction line 1 are revised to the improvement contents extracted bythe extracting section 15, whether or not a trouble occurs in theproduction line 1.

[0073] The feedback control section 18 transmits a feedback controlsignal for revising the production conditions for the production line 1in accordance with the improvement contents, to the production conditioncontrol section 9 when the correctness of the quality deteriorationfactor and the validity of the improvement contents are verified by theverifying section 17.

[0074] The feedback control signal transmitted from the feedback controlsection 18 is sent also to, for example, a CAD (computer aided design)of a production design division 22. Therefore, upon reception of thefeedback control signal indicating the improvement contents, theproduction design division 22 can reflect the improvement contents tothe designing of the production line 1 with use of the CAD.

[0075] The regional feedback control section 19 receives the productquality data 21 stored in the production history database 12 and thequality deterioration event in the production line 1, which is extractedby the extracting section 15, controls the production line 1 regionally,for example, controls only the temperature of the resist to anappropriate value, and notifies a warning or the like if necessarydepending on the quality deterioration event.

[0076] The regional feedback control section 19 controls each andindividual production condition to fall within a set value range. Thus,those quality deterioration factors which can be relatively easilysolved can be overcome.

[0077] However, in some cases, there are other quality deterioratingfactors which cannot be overcome even if each individual productioncondition is controlled by the regional feedback control section 19.These factors are, as mentioned above, a sudden variation of theoccurrence rate of the quality deterioration event and a yield stayingat its original level.

[0078] The apparatus of the present invention performs the qualitycontrol operation when a sudden variation of the occurrence rate of thequality deterioration event or staying of a yield at its original leveloccurs.

[0079] The operation of the apparatus having the above-describedstructure will now be described by following the procedure of theautomatic quality control program shown in FIG. 3.

[0080] The production line 1 is designed to manufacture color cathoderay tubes as shown in FIG. 2 through the panel mask assembly process 2,the black dye application process 3, the micro-filter applicationprocess 4, the fluorescent material application process 5, thesealing/enclosing/exhaustion process 6, the yoke assembly adjustmentprocess 7 and the examination process 8 in order.

[0081] While the production line 1 is in operation, the monitoringsection 14, in step #1, monitors production condition data from each ofa plurality of processes in the line 1 for color cathode ray tube shownin, for example, FIG. 2, such as the black dye application process 3,the micro-filter application process 4 and the fluorescent materialapplication process 5.

[0082] Here, the production condition data include, as shown in FIG. 4,for example, the serial number (serial No.), the date, the outsidetemperature, the humidity, the hot water ejecting time, the kineticviscosity of the fluorescent material slurry, the application amount ofthe fluorescent material slurry, the machine number of the device usedfor a respective process, the physical property of the liquid agent andthe like.

[0083] At the same time, the monitoring section 14 monitors productquality data from each of a plurality of processes in the productionline 1 for color cathode ray tube shown in, for example, FIG. 2, such asthe fluorescent material application process 5 and the examinationprocess 8.

[0084] The product quality data from the fluorescent materialapplication process 5 includes, for example, data regarding splashing ofthe fluorescent material while applying the fluorescent material slurryonto the glass panel of a color cathode ray tube, attachment of dust,irregularity of the application of the fluorescent material and bubblescreated while applying the slurry. Three colors of fluorescentmaterials, namely, R (red), G (green) and B (blue) are applied.

[0085] Regarding the product quality data 21, if there is an error in,for example, a color cathode ray tube, an error code which indicates adeterioration event of the error is stored in the production historydatabase 12.

[0086] Next, the monitoring section 14, in step #2, stores theproduction condition data 20 and the product quality data 21 monitored,in the production history database 12.

[0087] In the case where data are to be stored in the production historydatabase 12, if the production condition data and the product qualitydata are documents, the monitoring section 14 creates an electronic file14 a (electronified document) from the documents, and stores it in theproduction history database 12.

[0088] If the production condition data and the product quality data aresensor signals, the monitoring section 14 monitors the sensor signalsand converts them into digital signals (digital sensor signals 14 b),and stores the digital signal in the production history database 12.

[0089] If the production condition data and the product quality data areimages, the monitoring section 14 carries out pattern recognition 14 con the images, and stores them in the production history database 12.

[0090] If the production condition data and the product quality data aresensed amount by human (operator), the monitoring section 14 convertsthe sensed amount into a numerical value (conversion of sensed amountinto numeral 14 d) according to a specific algorithm, and stores it inthe production history database 12.

[0091] Next, the extracting section 15, in step #3, sections the productquality data 21 stored in the production history database 12 and detectsif there is a sudden variation in the occurrence rate of the qualitydeterioration event, or whether or not the yield of the color cathoderay tubes stays at the level of the original yield.

[0092] When the extracting section 15 detects that there is a suddenvariation in the occurrence rate of the quality deterioration event, orthe yield of the color cathode ray tubes stays at the level of theoriginal yield, the extracting section 15, in step #4, executes a datamining algorithm on the bases of the quality deterioration event and theproduction condition data 20, and extracts the quality deteriorationfactor which causes the quality deterioration event and the improvementcontents of the production condition data 20 with regard to the qualitydeterioration factor.

[0093] For example, when the extracting section 15 checks the productquality data 21 stored in the production history database 12 and detectsthat there is a sudden variation in the occurrence rate of the errorcode indicating the irregularity of the red fluorescent material, theextracting section 15 executes the data mining algorithm on the bases ofthe irregularity of the red fluorescent material (quality deteriorationevent) and the production condition data 20, and extracts the qualitydeterioration factor which causes the irregularity of the redfluorescent material and the improvement contents thereof.

[0094] More specifically, in the case where the outside temperature islow at the point when glass panels before the application of thefluorescent materials are loaded, and the kinetic viscosity of the redfluorescent material slurry is high, the extracting section 15 extractsthat the irregularity of the red fluorescent material frequently occurs,as well as the improvement contents therefor, that is, the temperatureat the point when the glass panels are loaded and the kinetic viscosityof the red fluorescent material are adjusted.

[0095] Next, the validity confirming section 16, in step #5, collatesthe quality deterioration factor and the improvement contents extractedfrom the extracting section 15 with the quality improvement history datapre-stored in the quality deterioration history database 13, in order toconfirm the validity of the quality deterioration factor and theimprovement contents.

[0096] After that, the verifying section 17, in step #6, executes asimulation of a phenomenon regarding the production line 1 according tothe quality deterioration factor and the improvement contents extractedby the extracting section 15, that is, a simulation for analyzing abasic physiochemical phenomenon regarding the manufacture of colorcathode ray tubes. From the result of the simulation, the correctness ofthe quality deterioration factor and the validity of the improvementcontents are verified.

[0097] In other words, the verifying section 17 verifies if the qualitydeterioration factor extracted by the extracting section 15 is correct.The section further verifies, when the production condition data of theproduction line 1 are revised to the improvement contents extracted bythe extracting section 15, whether or not a trouble occurs in theproduction line 1.

[0098] More specifically, the verifying section 17 executes a simulationof the fluorescent material application process 5, and obtains thefollowing simulation results. That is, when glass panels having a verylow temperature, which is caused by a low outside temperature, areloaded, the temperature of each glass panel becomes uneven from oneplace to another within it until it reaches the fluorescent materialapplication process 5. When a fluorescent material having a high kineticviscosity is injected in the above-described state, an irregularity iscreated in the fluorescent material film. Further, if the hot waterinjecting time which can adjust the temperature of each glass isextended and the upper limit value of the kinetic viscosity of thefluorescent material slurry is lowered so as to improve the abovesituation, there will creates no problem as a basic physiochemicalphenomenon of the application of a fluorescent material.

[0099] Thus, the verifying section 17 confirms the correctness of thequality deterioration factor and the validity of the improvementcontents when the deterioration factors (low outside temperature andhigh kinetic viscosity) for the past quality deterioration contents(frequent occurrence of irregularity of the red fluorescent material)and the improvement contents (extension of hot water ejection andrevision of the upper limit of the kinetic viscosity), which are storedin the quality improvement history database 13, match with thesimulation results described above.

[0100] Next, the feedback control section 18, in step #7, transmits afeedback control signal for revising the production conditions for theproduction line 1 in accordance with the improvement contents, to theproduction condition control section 9 when the correctness of thequality deterioration factor and the validity of the improvementcontents are verified by the verifying section 17.

[0101] For example, the feedback control section 18 transmits thefeedback control signal indicating the improvement contents, that is,the extension of the hot water ejecting time for stabilizing thetemperature of the glass panel of each color cathode ray tube, and thelowering of the upper limit value of the kinetic viscosity of thefluorescent material slurry.

[0102] Then, upon reception of the feedback control signal, theproduction condition control section 9 extends the hot water ejectingtime in the fluorescent material application process 5 and lowers theupper limit value of the kinetic viscosity of the fluorescent materialslurry.

[0103] The regional feedback control section 19 receives the productquality data 21 stored in the production history database 12 and thequality deterioration event in the production line 1, which is extractedby the extracting section 15, controls the production line 1 regionally,for example, controls only the temperature of the resist to anappropriate value, and notifies a warning or the like if necessarydepending on the quality deterioration event.

[0104] As described above, in the first embodiment, the productioncondition data 20 and the product quality data 21 in the production line1 are monitored, and stored in the production history database 12. Whilechecking the product quality data 21, if a sudden variation in theoccurrence rate of the quality deterioration event or the staying of ayield at its original level is detected in the production line 1, thequality deterioration factor and the improvement contents are extractedon the basis of the quality deterioration event and the productioncondition data 20. Then, the extracted results are collated with thequality improvement history data pre-stored so as to confirm thevalidity thereof, and further a simulation of a phenomenon regarding theproduction line 1 according to the quality deterioration factor and theimprovement contents is executed so as to verify the correctnessthereof. When the validity and correctness are verified, the productionconditions are revised in accordance with the improvement contents.

[0105] That is, a series of operations, that is, monitoring and makingdatabase of production history data, checking of quality data,extraction of quality deterioration factor and improvement contents,confirmation of the validity/correctness of the factor and improvementcontents and feedback of the result to the production conditions forimprovement, can be continuously carried out in cycles by means ofsoftware.

[0106] In this manner, it is possible to achieve an automatic qualitycontrol which can effectively make a full use of a huge amount of databy overcoming the limit of the data processing capability by the humansystem or the ambiguity innate to human empirical rule or intuition.

[0107] Thus, it is possible to achieve an automatic quality controlwhich can effectively make a full use of a huge amount of data obtainedby monitoring the production condition data 20 and the product qualitydata 21.

[0108] It should be noted here that a result still in progress in theabove-described automatic cycle by way of software can be utilized for aregional feedback control, the management of the human system or thelike. Further, the result of the verification obtained from thesimulation can be fed back to the designing of the subsequent product.

[0109] Next, the second embodiment of the present invention will now bedescribed with reference to an accompanying drawing. The same structuralparts as those shown in FIG. 1 are designated by the same referencenumerals, and the detailed descriptions therefor will be omitted here.

[0110]FIG. 6 is a block diagram showing a structure of an automaticquality control apparatus of a production line. In this apparatus, awarning section 30 and a revision expediting section 31 are provided inplace of the feedback control section 18 shown in FIG. 1.

[0111] The warning section 30 and the revision expediting section 31 areoperated when the validity confirming section 16 cannot confirm thevalidity of the quality deterioration factor and the improvementcontents, and the verifying section 17 cannot verify the correctness ofthe quality deterioration factor and the validity of the improvementcontents.

[0112] The warning section 30 output a warning indicating that it hasnot been able to confirm the validity and correctness.

[0113] The revision expediting section 31 presents candidates for thequality deterioration factor and requests revision of the productionconditions of the line 1 for improving the quality deterioration factor.

[0114] In addition to those procedures shown in FIG. 3, the automaticquality control program stored in the program memory 11 includes aprocedure in which when the validity of the quality deterioration factorand the improvement contents cannot be confirmed in the fifth procedure,and the correctness of the quality deterioration factor and the validityof the improvement contents cannot be verified in the sixth procedure, awarning indicating that it has not been able to confirm the validity andcorrectness is output. The program further includes a procedure in whichcandidates for the quality deterioration factor are presented andrevision of the production conditions of the line for improving thequality deterioration factor is requested.

[0115] With the above-described structure, when the validity of thequality deterioration factor and the improvement contents cannot beconfirmed by the validity confirming section 16, and the correctness ofthe quality deterioration factor and the validity of the improvementcontents cannot be verified by the verifying section 17, the warningsection 30 outputs a warning indicating that it has not been able toconfirm the validity and correctness.

[0116] Meanwhile, the revision expediting section 31 presents candidatesfor the quality deterioration factor and requests revision of theproduction conditions of the line 1 for improving the qualitydeterioration factor.

[0117] Thus, an instruction for revising the production conditions ofthe line 1 for improving the quality deterioration factor is given tothe operator. The operator revises the production conditions of theproduction line 1 for improving the quality deterioration factor.

[0118] In the first embodiment already described, candidates of thequality deterioration factor automatically extracted by various types ofthe data mining algorithms are difficult to understand in terms of theconventional concept, and further they cannot be estimated from ageneral physiochemical phenomenon. Therefore, when there is a truequality deterioration factor, the improvement by the automatic feedbackis not initiated.

[0119] On the other hand, in the second embodiment, when candidates forthe quality deterioration factor are automatically extracted by therevision expediting section 31, the operator is required to make ajudgment whether or not the production conditions should be revised tosolve the quality deterioration factor.

[0120] Thus, in addition to the effect of the first embodiment, thesecond embodiment can enhance the robustness of the system in acooperation with human system and can increase the rates of theoperations of the examination, finding and improvement of the qualitydeterioration factor, as compared to the conventional operations whichare conducted only by the human system.

[0121] Next, the third embodiment of the present invention will now bedescribed with reference to an accompanying drawing. The same structuralparts as those shown in FIG. 6 are designated by the same referencenumerals, and the detailed descriptions therefor will be omitted here.

[0122]FIG. 7 is a block diagram showing a structure of an automaticquality control apparatus of a production line. This apparatus includesa leaning section 32. When the production line 1 is improved by revisingthe production conditions of the line 1 in accordance with theimprovement contents as the revision is expedited by the revisionexpediting section 31 or the feedback control section 18, theimprovement example is additionally stored in the quality improvementhistory database 13.

[0123] In addition to those procedures shown in FIG. 3, the automaticquality control program stored in the program memory 11 includes aprocedure in which when the production line 1 is improved by revisingthe production conditions of the line 1 in accordance with theimprovement contents by the seventh procedure, the improvement exampleis leaned.

[0124] It is also possible to add to this automatic quality controlprogram a procedure in which when the validity of the qualitydeterioration factor and the improvement contents cannot be confirmed inthe fifth procedure, and the correctness of the quality deteriorationfactor and the validity of the improvement contents cannot be verifiedin the sixth procedure, a warning indicating that it has not been ableto confirm the validity and correctness is output, and another procedurein which candidates for the quality deterioration factor are presentedand revision of the production conditions of the line for improving thequality deterioration factor is requested.

[0125] With the above-described structure, the feedback control section18 transmits a feedback control signal for revising the productionconditions for the production line 1 in accordance with the improvementcontents, to the production condition control section 9 when thecorrectness of the quality deterioration factor and the validity of theimprovement contents are verified by the verifying section 17.

[0126] The production condition control section 9 controls each of aplurality of production conditions in the production line 1 forproducing color cathode ray tubes.

[0127] In the meantime, when the validity of the quality deteriorationfactor and the improvement contents cannot be confirmed by the validityconfirming section 16, and the correctness of the quality deteriorationfactor and the validity of the improvement contents cannot be verifiedby the verifying section 17, the warning section 30 outputs a warningindicating that it has not been able to confirm the validity andcorrectness.

[0128] Further, the revision expediting section 31 presents candidatesfor the quality deterioration factor and requests revision of theproduction conditions of the line 1 for improving the qualitydeterioration factor.

[0129] Thus, an instruction for revising the production conditions ofthe line 1 for improving the quality deterioration factor is given tothe operator. The operator revises the production conditions of theproduction line 1 for improving the quality deterioration factor.

[0130] When the production line 1 is improved by revising the productionconditions of the line 1 in accordance with the improvement contents asthe revision is expedited by the revision expediting section 31 or thefeedback control section 18, the leaning section 32 additionally storesthe improvement example in the quality improvement history database 13.

[0131] In the case where the automatic quality control system and humancooperate together to improve a totally unknown quality deteriorationfactor, by additionally storing the occurrence of already known errors,finding of the factor for the lowering of the yield and the improvementexample, the performance of the self leaning of the automatic qualitycontrol device from then onwards can be improved.

[0132] Further, the self-leaning of the quality improvement method andthe enhancement of the performance can be achieved. From these results,it is possible to detect the quality deterioration factor in an earlystage and therefore it become able to make an improvement at an earlystage. Therefore, with the present invention apparatus, a productionline having a high and stable reliability can be established.

[0133] In addition, it is possible to find some other qualitydeterioration factors which have been hidden unknown, and therefore afurther improvement of the quality and yield can be expected.

[0134] It should be noted that the present invention is not limited tothe first to third embodiment, and therefore it is possible to remodelthe invention in various modifications in practicing it as long as theessence of the invention is maintained.

[0135] For example, in the third embodiment, when the qualitydeterioration factor is improved by revising the production condition,such an improvement example is additionally stored in the qualityimprovement history data 13.

[0136] Other than the above, it is alternatively possible to store dataof production conditions which cannot be allowed in the production ofthe products, in the quality improvement history data 12. With thesemeasures, those production conditions which must not be carried out arenot selected, and therefore a production line having a higher and morestable reliability can be established.

[0137] Additional advantages and modifications will readily occur tothose skilled in the art. Therefore, the invention in its broaderaspects is not limited to the specific details and representativeembodiments shown and described herein. Accordingly, variousmodifications may be made without departing from the spirit or scope ofthe general inventive concept as defined by the appended claims andtheir equivalents.

What is claimed is:
 1. An automatic quality control method for aproduction line, comprising: monitoring a plurality of productioncondition data for manufacturing products from a production line andproduct quality data indicating quality of manufactured products;storing the production condition data and product quality data thusmonitored in a database; checking the production condition data todetect whether or not there is an event which deteriorates the qualityof products; extracting, if a quality deteriorating event is detected, aquality deteriorating factor which causes the quality deterioratingevent and improvement contents of production conditions against thequality deteriorating factor on the basis of the quality deterioratingevent and the production condition data; collating the qualitydeteriorating factor and improvement contents thus extracted withimprovement examples pre-stored for possible quality deterioratingfactors and confirming the validity of the quality deteriorating factorand improvement contents; executing a simulation of manufacture of aproduct in the production line based on the quality deteriorating factorand improvement contents thus extracted, and verifying the correctnessof the quality deteriorating factor and the validity of the improvementcontents, extracted from the result of the simulation; and if thecorrectness of the quality deteriorating factor and the validity of theimprovement contents are verified, the production conditions for theproduction line in accordance with the improvement contents.
 2. Anautomatic quality control method according to claim 1, wherein saidmonitoring step comprises monitoring of the production condition dataand the product quality data in the production line including aplurality of processes for each process.
 3. An automatic quality controlmethod according to claim 1, wherein the product quality data includes ajudgment result indicating whether or not the products thus producedeach have a preset production result, an examination result indicatingwhether or not the products each have pre-designed appearance andfunction, and a quality indicating a yield of the products produced. 4.An automatic quality control method according to claim 1, wherein saidchecking step includes detecting a sudden variation in an occurrencerate of the quality deterioration event and a yield of the productstaying at its original yield while checking the product quality data.5. An automatic quality control method according to claim 1, whereinsaid extracting step includes executing a data mining algorithm based onthe quality deterioration event and the production condition data andthereby to extract the quality improvement factor and the improvementcontents.
 6. An automatic quality control method according to claim 1,further comprising controlling the production conditions for theproduction line individually within respective specific values uponreception of the product quality data and the quality deteriorationevent.
 7. An automatic quality control method according to claim 1,further comprising, when the validity of the quality deteriorationfactor and the improvement contents is not confirmed in said collatingstep, and the correctness of the quality deterioration factor and thevalidity of the improvement contents are not verified in said executingand verifying step: outputting a warning indicating that the validityand correctness have not been confirmed; and presenting candidates forthe quality deterioration factor and requesting revision of theproduction conditions for the production line to solve the qualitydeterioration factor.
 8. An automatic quality control method accordingto claim 1, wherein said executing and verifying step includes:verifying the validity of the quality deterioration factor extractedfrom the simulation result; and verifying the validity of theimprovement contents by judging whether or not a problem occurs in theproduction line when the production condition data for the productionline are revised in accordance with the improvement contents.
 9. Anautomatic quality control method according to claim 1, furthercomprising: learning an improvement example when the production line hasbeen improved after the production conditions of the production linehave been revised in accordance with the improvement contents in saidrevising step.
 10. An automatic quality control apparatus for aproduction line, comprising: a production line configured to produceproducts; a first database configured to store a plurality of productioncondition data for producing the products and product quality dataindicating quality of the products; a monitoring section configured tomonitor a plurality of production condition data for product theproducts from the production line and further monitor the productquality data indicating the quality of the products, to store them inthe first database; an extraction section configured to check theproduction condition data to detect whether or not there is an eventwhich deteriorate the quality of products, and to extract a qualitydeteriorating factor which causes the quality deteriorating event andimprovement contents of production conditions regarding the qualitydeteriorating factor on the basis of the quality deteriorating event andthe production condition data; a second database configured to store, inadvance, improvement examples for the quality deterioration factor; avalidity confirming section configured to confirm the validity of thequality deteriorating factor and improvement contents by collating thequality deteriorating factor and improvement contents extracted by theextracting section with the improvement examples pre-stored in thesecond database; a verifying section configured to execute a simulationof production of the products in the production line under currentproduction conditions, and to verify the correctness of the qualitydeteriorating factor and the validity of the improvement contents from aresult of the simulation; and a feedback control section configured torevise the production conditions for the production line in accordancewith the improvement contents when the correctness of the qualitydeteriorating factor and the validity of the improvement contents areverified.
 11. An automatic quality control apparatus for a productionline, according to claim 10, wherein the first data base configured tostore the product condition data, a judgment result indicating whetheror not the products thus produced each have a preset production result,an examination result indicating whether or not the products each havepre-designed appearance and function, and the product quality dataindicating a yield of the products produced.
 12. An automatic qualitycontrol apparatus for a production line, according to claim 10, whereinthe extracting section configured to detect a sudden variation in anoccurrence rate of the quality deterioration event and a yield of theproduct staying at its original yield while checking the product qualitydata.
 13. An automatic quality control apparatus for a production line,according to claim 10, wherein the extracting section configured toexecute a data mining algorithm based on the quality deterioration eventand the production condition data and thereby to extract the qualityimprovement factor and the improvement contents.
 14. An automaticquality control apparatus for a production line, according to claim 10,further comprising: a warning section configured to output a warningindicating that the validity and correctness have not been confirmed,when the validity of the quality deterioration factor and theimprovement contents are not confirmed in said validity confirmingsection, and the correctness of the quality deterioration factor and thevalidity of the improvement contents are not verified in the verifyingsection; and a revise expediting section configured to presentcandidates for the quality deterioration factor and to request revisionof the production conditions for the production line to solve thequality deterioration factor.
 15. An automatic quality control apparatusfor a production line, according to claim 10, further comprising: alearning section configured to lean an improvement example when theproduction line has been improved after the production conditions of theproduction line have been revised in accordance with the improvementcontents by the feedback control section.
 16. An automatic qualitycontrol program for a production line, comprising: monitoring aplurality of production condition data for manufacturing color cathoderay tubes from a production line and product quality data indicatingquality of manufactured products; storing the production condition dataand product quality data thus monitored in a database; checking theproduction condition data to detect whether or not there is an eventwhich deteriorate the quality of products; extracting, if a qualitydeteriorating event is detected, a quality deteriorating factor whichcauses the quality deteriorating event and improvement contents ofproduction conditions against the quality deteriorating factor on thebasis of the quality deteriorating event and the production conditiondata; collating the quality deteriorating factor and improvementcontents thus extracted with improvement examples pre-stored forpossible quality deteriorating factors and confirming the validity ofthe quality deteriorating factor and improvement contents; executing asimulation of manufacture of a product in the production line based onthe quality deteriorating factor and improvement contents thusextracted, and verifying the correctness of the quality deterioratingfactor and the validity of the improvement contents, extracted from theresult of the simulation; and if the correctness of the qualitydeteriorating factor and the validity of the improvement contents areverified, the production conditions for the production line inaccordance with the improvement contents.
 17. An automatic qualitycontrol program according to claim 16, further comprising: outputting awarning indicating that the validity and correctness have not beenconfirmed, when the validity of the quality deterioration factor and theimprovement contents is not confirmed in said collating and confirmingprocedure, and the correctness of the quality deterioration factor andthe validity of the improvement contents are not verified in saidexecuting and verifying procedure; and presenting candidates for thequality deterioration factor and requesting revision of the productionconditions for the production line to solve the quality deteriorationfactor.
 18. An automatic quality control program according to claim 16,wherein said executing and verifying procedure includes: verifying thevalidity of the quality deterioration factor extracted from thesimulation result; and verifying the validity of the improvementcontents by judging whether or not a problem occurs in the productionline when the production condition data for the production line arerevised in accordance with the improvement contents.
 19. An automaticquality control program according to claim 16, further comprising:learning an improvement example when the production line has beenimproved after the production conditions of the production line havebeen revised in accordance with the improvement contents in saidrevising procedure.